Percentage deviation from rolling VWAP.
Positive values indicate price > VWAP (bullish pressure/premium).
Negative values indicate price < VWAP (bearish pressure/discount).
Source code in src/quantmaster/features/microstructure.py
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186 | def vwap_deviation(
data: pd.DataFrame,
*,
window: int = 20,
price_col: str = "close",
volume_col: str = "volume",
) -> pd.Series:
"""
Percentage deviation from rolling VWAP.
Positive values indicate price > VWAP (bullish pressure/premium).
Negative values indicate price < VWAP (bearish pressure/discount).
"""
window = validate_positive_int(window, name="window")
validate_columns(data, required=(price_col, volume_col))
price = get_price_series(data, price_col=price_col).astype(float)
volume = pd.to_numeric(data[volume_col], errors="coerce").astype(float)
pv = price * volume
cum_pv = pv.rolling(window).sum()
cum_v = volume.rolling(window).sum()
vwap = cum_pv / cum_v
# Deviation %
dev = (price - vwap) / vwap
out = dev * 100.0
out.name = f"vwap_deviation_{window}"
return out
|